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Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets
Institution:1. Associate Professor, Dept of Environment and Society, Utah State University, Logan, UT 84322, USA;2. Consultant, MARIL PLC, Addis Ababa, Ethiopia;1. Range Ecologist, Arctic Slope Regional Corporation Research & Technology Solutions, Contractor to US Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD 57198, USA;2. Professor, Department of Natural Resource Management, South Dakota State University, Brookings, SD 57007, USA;3. Research Physical Scientist, US Geological Survey Earth Resources Observation and Science Center, Sioux Falls, SD 57198, USA;4. Graduate Research Assistant, Department of Natural Resource Management, South Dakota State University, Brookings, SD 57007, USA.;1. Associate Professor, Key Laboratory of Grassland Ecosystem of Ministry of Education/Rangeland Sciences Department, Gansu Agricultural University/Sino-U.S. Centers for Grazing Land Ecosystem Sustainability, Lanzhou, 730070, China;2. PhD Student, Key Laboratory of Grassland Ecosystem of Ministry of Education/Rangeland Sciences Department, Gansu Agricultural University/Sino-U.S. Centers for Grazing Land Ecosystem Sustainability, Lanzhou, 730070, China, Institute of Animal and Veterinary Science, Bijie, 551700, China;3. Visiting Professor, Key Laboratory of Grassland Ecosystem of Ministry of Education/Rangeland Sciences Department, Gansu Agricultural University/Sino-U.S. Centers for Grazing Land Ecosystem Sustainability, Lanzhou, 730070, China;4. Masters Student, Key Laboratory of Grassland Ecosystem of Ministry of Education/Rangeland Sciences Department, Gansu Agricultural University/Sino-U.S. Centers for Grazing Land Ecosystem Sustainability, Lanzhou, 730070, China
Abstract:
Keywords:social-ecological systems  common pool resources  complexity  non-linearity  artificial neural networks  large-N
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